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Record W2114471037 · doi:10.1061/9780784413067.076

Ship Loader Platforms Using a Pile/Micropile System

2013· article· en· W2114471037 on OpenAlexaff
Jon Mjelde, Bill Allen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsBerger (Canada)
Fundersnot available
KeywordsPileEngineeringShipyardBoomTension (geology)Geotechnical engineeringLoaderStructural engineeringUltimate tensile strengthMarine engineeringShipbuildingMechanical engineering

Abstract

fetched live from OpenAlex

In 2008, a condition survey indicated that major structural improvements were necessary to extend the service life of the 50-year-old United Harvest grain import/export dock located on the Columbia River at the Port of Kalama in Kalama, Washington. Rather than repair the dock, the owner elected to replace it, modernize the dockside grain-handling equipment, and install two 150-foot [45.7 m] boom fixed-tower ship loaders to increase the ship loading rate from 1,200 metric tons per hour (mtph) [1,323 short tons per hour (stph)] to 3,200 mtph [3,527 stph]. To support the towers and resist the ship berthing and mooring loads, two new batter pile-supported concrete platforms were constructed. Because the riverbed at the site consisted of approximately 65 feet [20 m] of highly liquefiable sand over solid basalt, a micropile was installed inside each batter pile and pretensioned into the basalt to resist the high-tension loads on the piles. By setting the lock-off load equal to just greater than the maximum non-seismic tensile demand of each pile, the micropile force/displacement response exhibited a bilinear behavior under tensile loads. The tensile strain of the pile/micropile system increases when the non-seismic forces are overcome, and this behavior is used to reduce seismic forces on the platform. This paper focuses on the selection of the fixed-tower ship loaders, the design of the ship loader platforms, and the pile/micropile bilinear response and its incorporation into the design per the International Building Code (IBC).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.169
Teacher spread0.159 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

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